PROJECT SUMMARY/ABSTRACT Autism spectrum disorder (ASD) prevalence has increased over several decades to its current estimated prevalence of 1.5% among 8-year-old children in the United States. Recent research suggests that adverse child neurodevelopmental outcomes, including ASD, may occur in association with maternal obesity and diabetes during pregnancy. Both obesity and diabetes mellitus among women of reproductive age have been increasing and could contribute to the increase in ASD prevalence. Moreover, ambient air pollution (AP), a ubiquitous urban environmental exposure, has been associated with diabetes, including a small number of studies of gestational diabetes mellitus (GDM), and with ASD. Furthermore, there is growing evidence of other neurotoxic effects of AP and potential overlapping biological mechanisms for effects of AP and diabetes. However, there are few prospective population-based studies with high quality outcome and exposure data that have addressed the relationship between AP, GDM, and ASD, and results have not been consistent. The proposed study?s main objective is to assess the relationship of AP to GDM and ASD, including effects of joint exposure to AP and GDM on ASD, using data from a large Kaiser Permanente Southern California (KPSC) pregnancy cohort study that showed that maternal GDM was associated with ASD. The aims are: 1) to evaluate the association between prenatal exposure to AP and ASD risk; 2) to examine whether prenatal exposure to AP is also associated with GDM; and 3) to assess whether GDM modifies or mediates the association between prenatal exposure to AP and ASD risk. These aims will be addressed using electronic medical records data from the existing cohort of children born in KPSC hospitals between 1995 and 2013. Gestational and early life exposure to traffic density and residential proximity to major roadways (markers for the near-roadway air pollution mixture), and to regional particulate and gaseous air pollutants will be estimated for approximately 80,000 mother-offspring pairs using a low-cost procedure developed by the National Institute of Environmental Health Sciences (NIEHS)-supported Southern California Environmental Health Sciences Center. Both Cox regression and logistic regression models will be used to examine the associations of AP, GDM, and ASD. The proposed training plan will result in depth of knowledge of neuroepidemiology, specifically ASD, AP exposure assessment, and of statistical analyses necessary for a career as an independent investigator conducting interdisciplinary epidemiologic research on environmental factors contributing to pediatric neurological disorders. The study addresses the NIEHS goal to understand the effects of environmental factors during vulnerable periods that increase the risk of ASD. Furthermore, this study has the potential to address gaps in our understanding of the effects of role of AP in GDM and ASD. AP and GDM are common risk factors amenable to intervention targeting public policy and behavior.